Wipe sampling variables were evaluated to determine their effects on recovery results for commonly misused pesticides on surfaces. This dataset is associated with the following publication: Willison, S., D. Stout, A. Mysz, J. Starr, D. Tabor, B. Wyrzykowska, J. Nardin, E. Morris, and E. Snyder. Evaluating Wipe Sampling Parameters to Assess Method Performance and Data Confidence during Remediation of Hazardous Pesticide Misuse Chemicals on Indoor Materials. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 856(1): 159053, (2023).

Wipe sampling variables were evaluated to determine their effects on recovery results for commonly misused pesticides on surfaces. This dataset is associated with the following publication: Willison, S., D. Stout, A. Mysz, J. Starr, D. Tabor, B. Wyrzykowska, J. Nardin, E. Morris, and E. Snyder. Evaluating Wipe Sampling Parameters to Assess Method Performance and Data Confidence during Remediation of Hazardous Pesticide Misuse Chemicals on Indoor Materials. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 856(1): 159053, (2023).

These data sets are time, precipitation, inflow, outflow.and depth for various LID studies.

These data sets are time, precipitation, inflow, outflow.and depth for various LID studies.

These datasets outline the previously published studies, the parameters measured and optimized, and the results of the PEST optimization of SWMM. NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person. This dataset is not publicly accessible because: Data removed from dataset due to revocation. Please refer inquiries regarding this dataset to the listed contact person. It can be accessed through the following means: N/A. Format: N/A. This dataset is associated with the following publication: Platz, M., M. Simon, and M. Tryby. Testing of Storm Water Management Model Low Impact Development Modules. JAWRA. American Water Resources Association, Middleburg, VA, USA, 56(2): 283-296, (2020).

,This dataset includes all the data and R code needed to reproduce the analyses in a forthcoming manuscript:,Copes, W. E., Q. D. Read, and B. J. Smith. Environmental influences on drying rate of spray applied disinfestants from horticultural production services. PhytoFrontiers, DOI pending.,Study description: Instructions for disinfestants typically specify a dose and a contact time to kill plant pathogens on production surfaces. A problem occurs when disinfestants are applied to large production areas where the evaporation rate is affected by weather conditions. The common contact time recommendation of 10 min may not be achieved under hot, sunny conditions that promote fast drying. This study is an investigation into how the evaporation rates of six commercial disinfestants vary when applied to six types of substrate materials under cool to hot and cloudy to sunny weather conditions. Initially, disinfestants with low surface tension spread out to provide 100% coverage and disinfestants with high surface tension beaded up to provide about 60% coverage when applied to hard smooth surfaces. Disinfestants applied to porous materials were quickly absorbed into the body of the material, such as wood and concrete. Even though disinfestants evaporated faster under hot sunny conditions than under cool cloudy conditions, coverage was reduced considerably in the first 2.5 min under most weather conditions and reduced to less than or equal to 50% coverage by 5 min.,Dataset contents: This dataset includes R code to import the data and fit Bayesian statistical models using the model fitting software CmdStan, interfaced with R using the packages brms and cmdstanr. The models (one for 2022 and one for 2023) compare how quickly different spray-applied disinfestants dry, depending on what chemical was sprayed, what surface material it was sprayed onto, and what the weather conditions were at the time. Next, the statistical models are used to generate predictions and compare mean drying rates between the disinfestants, surface materials, and weather conditions. Finally, tables and figures are created.,These files are included:,,

This data release contains two tables-one table of field spike recovery data and one table of lab reagent spike recovery data-for pesticides and pesticide degradates analyzed by the USGS National Water Quality Laboratory (NWQL) schedule 2437, and associated metadata. The table of field spike recovery data includes results from paired environmental and spike samples collected by the National Water Quality Program, National Water-Quality Assessment (NAWQA) Project in surface water. The table of lab reagent spike data contains quality-control sample information stored in the NWQL database. Both tables include fields for data-quality indicators that are described in the data processing steps of the metadata file. The tables in this data release contain data for water years 2016-17 and were developed as a follow-up to the analysis for water years 2013-15 conducted by Shoda and others (2017 and 2018). Shoda, M.E., Nowell, L.H., Stone, W.W., Sandstrom, M.W., and Bexfield, L.M., 2018, Data analysis considerations for pesticides determined by National Water Quality Laboratory schedule 2437: U.S. Geological Survey Scientific Investigations Report 2018-5007, 458 p., https://doi.org/10.3133/sir20185007. Shoda, M.E., Nowell, L.H., Bexfield, L.M., Sandstrom, M.W., Stone, W.W., 2017, Recovery data for surface water, groundwater and lab reagent samples analyzed by the USGS National Water Quality Laboratory schedule 2437, water years 2013-15: U.S. Geological Survey data release, https://doi.org/10.5066/F7QZ28G4.

This data release contains two tables-one table of field spike recovery data and one table of lab reagent spike recovery data-for pesticides and pesticide degradates analyzed by the USGS National Water Quality Laboratory (NWQL) schedule 2437, and associated metadata. The table of field spike recovery data includes results from paired environmental and spike samples collected by the National Water Quality Program, National Water-Quality Assessment (NAWQA) Project in surface water. The table of lab reagent spike data contains quality-control sample information stored in the NWQL database. Both tables include fields for data-quality indicators that are described in the data processing steps of the metadata file. The tables in this data release contain data for water years 2016-17 and were developed as a follow-up to the analysis for water years 2013-15 conducted by Shoda and others (2017 and 2018). Shoda, M.E., Nowell, L.H., Stone, W.W., Sandstrom, M.W., and Bexfield, L.M., 2018, Data analysis considerations for pesticides determined by National Water Quality Laboratory schedule 2437: U.S. Geological Survey Scientific Investigations Report 2018-5007, 458 p., https://doi.org/10.3133/sir20185007. Shoda, M.E., Nowell, L.H., Bexfield, L.M., Sandstrom, M.W., Stone, W.W., 2017, Recovery data for surface water, groundwater and lab reagent samples analyzed by the USGS National Water Quality Laboratory schedule 2437, water years 2013-15: U.S. Geological Survey data release, https://doi.org/10.5066/F7QZ28G4.